PDE Ingesting and Processing the Data Practice Question
A data engineer needs to create a Dataflow pipeline template that can be reused across multiple environments (dev, staging, prod) with different parameters (e.g., input Pub/Sub topic, output BigQuery table). Which template type should they use?
⚠ Common exam trap
The Google Cloud exam often tests the distinction between Classic Templates (compile-time parameterization) and Flex Templates (runtime parameterization), trapping candidates who assume all templates support the same level of parameter flexibility.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Flex Template
Flex Templates (B) are the correct choice because they package a Dataflow pipeline as a Docker image, allowing environment-specific parameters (e.g., Pub/Sub topic, BigQuery table) to be passed at runtime via the --parameters flag. This enables true reusability across dev, staging, and prod without modifying the template code, unlike Classic Templates which require compile-time parameterization.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Dataflow Prime
Why it's wrong here
Dataflow Prime is a resource optimization feature, not a template type.
- ✓
Flex Template
Why this is correct
Flex Templates support custom Docker images and runtime parameters, making them suitable for multi-environment reuse.
- ✗
Classic Template
Why it's wrong here
Classic templates lack the inherent parameterisation capabilities required to dynamically adjust configurations like Pub/Sub topics or BigQuery tables for different environments. While tempting due to their historical prevalence and straightforward creation for fixed pipelines, they are designed for static, single-purpose data processing jobs rather than the flexible, environment-agnostic reuse demanded by the scenario.
- ✗
Cloud Composer workflow template
Why it's wrong here
Cloud Composer is an orchestration tool, not a Dataflow template type.
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